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arXiv 2024年

作者： Zhang, Pengfei Li, Chang Zhang, Yongjun Qin, Rongjun Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province College of Urban and Environmental Science Central China Normal University Wuhan China School of Remote Sensing and Information Engineering Wuhan University China Department of Civil Environmental and Geodetic Engineering Department of Electrical and Computer Engineering Translational Data Analytics Institute The Ohio State University ColumbusOH United States

Remotely sensed imagery interpretation (RSII), including semantic segmentation and change detection, faces the three major problems: (1) objective representation of spatial distribution patterns with coexistence of spatial stationary and non-stationary;(2) edge uncertainty problem caused by downsampling encoder and intrinsic edge noises (e.g., mixed pixel and edge occlusion etc.);and (3) false detection problem caused by geometric registration error in change detection. To solve the aforementioned problems, uncertainty-diffusion-model-based high-Frequency TransFormer network (UDHF2-Net) is the first to be proposed, whose superiorities are as follows: (1) a spatially-stationary-and-non-stationary high-frequency connection paradigm (SHCP) is proposed to enhance the interaction of spatially frequency-wise stationary and non-stationary features to yield high-fidelity edge extraction result. Inspired by HRFormer, SHCP proposes high-frequency-wise stream to replace high-resolution-wise stream in HRFormer through the whole encoder-decoder process with parallel frequency-wise high-to-low streams, so it improves the edge extraction accuracy by continuously remaining high-frequency information;(2) a mask-and-geo-knowledge-based uncertainty diffusion module (MUDM), which is a self-supervised learning strategy, is proposed to improve the edge accuracy of extraction and change detection by gradually removing the simulated spectrum noises based on geo-knowledge and the generated diffused spectrum noises;(3) a frequency-wise semi-pseudo-Siamese UDHF2-Net is the first to be proposed to balance accuracy and complexity for change detection. Besides the aforementioned spectrum noises in semantic segmentation, MUDM is also a self-supervised learning strategy to effectively reduce the edge false change detection from the generated imagery with geometric registration error. In semantic segmentation experiments, UDHF2-Net achieved the best mIoU values of 92.00%, 87.31% and 55.27% respecti

关键词： Semantic Segmentation

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Spatiotemporal-Statistical-Modelling-Based Soil Loss Equation Calibration (Ssmbslec) by Air-Ground Collaboration

SSRN

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SSRN 2024年

作者： Li, Chang Yao, Jiayin Ding, Yijia Wu, Yijin Wu, JunZao Wu, Man Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province College of Urban and Environmental Science Central China Normal University Wuhan China Faculty of Resources and Environmental Science Hubei University Wuhan China Water and Soil Conservation Monitoring Station in Caidian District Wuhan China Water and soil conservation and planned water conservation station in Caidian District Wuhan China

The soil erosion module (SEM) calculated by the soil loss equation (SLE) is currently a computer simulation value, which may not be consistent with the actual value of field soil erosion. Therefore, it is necessary to calibrate the SEM to make it more approximate to the actual value. Additionally, due to the existence of spatiotemporal non-stationarity, traditional ordinary least squares (OLS) may not calibrate the deviation between the simulation value and actual value well. To address the aforementioned issues, this paper proposes the first spatiotemporal-statistical-modelling-based calibration method for a soil loss equation (SSMBSLEC) through air-ground collaboration. This method utilises data from unmanned aerial vehicles (UAVs) and ground monitoring stations to quantitatively calibrate the SEM. The experimental results from the Caidian District area demonstrate the effectiveness of this approach. The statistical calibration models were ranked in order of accuracy, from high to low, as follows: The study employed four regression techniques: geographically weighted regression, geographically and temporally weighted regression, temporally weighted regression, and OLS. The results of the hotspot analysis, based on space-time cubes, showed that the spatial law consistency between the actual value of soil erosion and SEM was the strongest, followed by the spatiotemporal law consistency, and the time consistency. These findings suggest that the accuracy of each SSMBSLEC model is affected by these factors. This study could enhance the methods and theory of water and soil conservation, promote interdisciplinary collaboration between it and spatial information science, and provide a research basis for the quantitative estimation of the actual value of SEM. © 2024, The Authors. All rights reserved.

关键词： Erosion

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Spatiotemporal process and mechanism of Kashin-Beck disease regression in Xizang during 2000-2015

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Dili Xuebao/Acta Geographica Sinica 2024年第11期79卷 2849-2863页

作者： Wang, Jing Li, Ruonan Wei, Binggan Li, Hairong Guo, Min Key Laboratory for Geographical Process Analysis & Simulation Research Institute of Sustainable Development Central China Normal University Wuhan430079 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research CAS Beijing100101 China Xizang Autonomous Region Center for Disease Control and Prevention Lhasa850030 China

Kashin-Beck disease (KBD) control in Xizang has now entered a new stage of consolidation and improvement. Clarifying the spatiotemporal mechanism of its regression is of great significance for promoting the long-term prevention and control of endemic diseases in the plateau. Based on the detection rate data of KBD in Xizang from 2000 to 2015 and by the methods of random forest and spatial statistics, this study analyzed the spatiotemporal variation characteristics of KBD and explored the main factors affecting the regression of KBD and their regional differences. The results showed that: (1) The condition of KBD decreased steadily in all parts of Xizang during 2000-2015. The spatial distribution of KBD gradually converged to the east from the overall pattern of high in the east and low in the west, high in the south and low in the north. The disease was the most serious and had the longest duration in Qamdo wards. (2) The top four major factors affecting the regression of KBD were per capita food consumption of farmers and herdsmen, per capita GDP, per capita disposable income of farmers and herdsmen, and NDVI. Except for NDVI, all the other factors showed negative correlations with the detection rate of KBD. (3) In Ali, the prevalence of KBD was mainly influenced by per capita GDP and the income level of farmers and herdsmen, while in the middle reaches of the Yarlung Zangbo River and Qamdo, wards were more affected by dietary factors. (4) The dominant factors for the prevalence of KBD varied greatly within different years, which specifically manifested as a shift from natural factors to humanistic and social factors. Social economy, dietary nutrition and land use patterns played important roles in the prevention and control of KBD in Xizang. In view of the unique environmental conditions in Xizang, strengthening diversified food supply and adhering to returning farmland to forests and grasslands are still the basic countermeasures for preventing and controlling KB

关键词： influence mechanism Kashin-Beck disease (KBD) random forest spatiotemporal variation Xizang

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High nitrogen fertilizer input enhanced the microbial network complexity in the paddy soil

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Soil Ecology Letters 2024年第2期6卷 97-109页

作者： Yanan Chen Yan Li Tianyi Qiu Haoran He Ji Liu Chengjiao Duan Yongxing Cui Min Huang Chunyan Wu Linchuan Fang The Research Center of Soil and Water Conservation and Ecological Environment Chinese Academy of Sciences and Ministry of EducationYangling712100China State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau Institute of Soil and Water Conservation CAS and MWRYangling712100China University of Chinese Academy of Sciences Beijing100049China Institute of Environment Resource and Soil Fertilizer Zhejiang Academy of Agricultural SciencesHangzhou310021China College of Natural Resources and Environment Northwest A&F UniversityYangling712100China Hubei Province Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhan430079China Department of Ecohydrology Leibniz Institute of Freshwater Ecology and Inland FisheriesBerlin12587Germany Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking UniversityBeijing100871China College of Resources and Environmental Engineering Wuhan University of TechnologyWuhan430070China CAS Center for Excellence in Quaternary Science and Global Change Xi’an710061China

N fertilizer altered bacterial community compositions by changing soil nutrients.•Bacterial ammonia oxidation became predominated with the increasing N rate.•Excessive N input caused the information of a more complex microbial network.•Intensified microbial competition by excessive N was due to negative link ***(N)fertilization drives the structure and function of soil microbial communities,which are crucial for regulating soil biogeochemical cycling and maintaining ecosystem *** the N fertilizer effects on soil microbial composition and diversity have been widely investigated,it is generally overlooked that ecosystem processes are carried out via complex associations among microbiome ***,we examined the effects of five N fertilization levels(0,135,180,225,and 360 kg N ha−1)on microbial co-occurrence networks and key functional taxa such as ammonia-oxidizers in paddy *** results showed that N addition altered microbial community composition,which were positively related to soil total N and available phosphorus(P)*** abundance of ammonia-oxidizing archaea(AOA)significantly decreased after N addition,whereas ammonia-oxidizing bacteria(AOB)increased in N360 *** with low-N group(N0 and N135),the high-N group(N225 and N360)shaped more complex microbial webs and thus improved the stability of the microbial *** least squares path modeling further revealed that N fertilizer had a higher effect on microbial network complexity in the high-N group(0.83)than the low-N group(0.49).Although there were more positive links across all microbial networks,the proportion of negative links significantly increased in the high-N network,suggesting that excess N addition aggravated the competition among microbial *** these interactions between microbial communities and N fertilization advances our understanding of biogeochemical processes in paddy soils and their effects on nutrient supply to

关键词： nitrogen fertilizer paddy soil co-occurrence network microbial interaction

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Measuring Network Configuration of the Yangtze River Middle Reaches Urban Agglomeration:Based on Modified Radiation Model

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Chinese geographical Science 2020年第4期30卷 677-694页

作者： ZHENG Wensheng KUANG Aiping WANG Xiaofang CHEN Jing Key Laboratory for Geographical Process Analysis&Simulation of Hubei Province Central China Normal UniversityWuhan 430079China Academy of Wuhan Metropolitan Area Hubei Development and Reform Commission&Central China Normal UniversityWuhan 430079China Hubei Institute of Economic and Social Development Central China Normal UniversityWuhan 430079China Wuhan Branch of China Tourism Academy Central China Normal UniversityWuhan 430079China

The objective of this study is to develop a framework for re-examining and re-defining the classical concepts of spatial interaction and reorganization in the urban *** introduce a modified radiation model for spatial interactions,coupled with migration big data,transport accessibility algorithm,and city competitiveness assessment for efficient distribution of the inter-city flow through the *** Yangtze River Middle Reaches(YRMR)urban agglomeration(UA)is chosen as the case study region to systematically identify and measure its spatial configuration and to gain insights for other UAs‘sustainable development in *** results are also compared with those computed by the classical gravity model to systematically discuss the applicability of spatial interaction laws and models,and related practical policies for regional sustainable development are discussed based on the findings as *** conclusions are highlighted below:1)Combining with the?city network paradigm‘and?central place theory‘can better express the spatial configurations of city systems in the context of?space of flows‘;2)The results validate the potentialities of a multi-analysis framework to assess the spatial configurations of city network based on the improved radiation model and network analysis tools;3)The applications of spatial interaction models should be considered according to the specific geographical entity and its spatial scale.

关键词： spatial interaction city network radiation model gravity model urban agglomeration

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Improved modeling and analysis of the patch size–frequency distribution of forest disturbances in China based on a Landsat forest cover change product

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International Journal of Digital Earth 2021年第2期14卷 181-201页

作者： Dan-Xia Song Chengquan Huang Tao He Joseph O.Sexton Ainong Li Sike Li Hao Wu John R.Townshend College of Urban and Environmental Sciences Central China Normal UniversityWuhanPeople’s Republic of China Hubei Provincial Key Laboratory for Geographical Process Analysis and Simulation Central China Normal UniversityWuhanPeople’s Republic of China Department of Geographical Sciences University of MarylandCollege ParkMDUSA School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China terraPulse IncGaithersburgMDUSA Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengduPeople’s Republic of China School of Earth Atmosphere and EnvironmentMonash University–Clayton CampusVictoriaAustralia

Forest disturbances have been altering the ecological properties of ecosystems;meanwhile,disturbance events of varying sizes create different structures and functions for a forest ***,size and frequency are important attributes of disturbances,and their relationship should be *** present a hierarchical method through the modeling of the overall trend of the size–frequency distribution and the characterization of the non-constant variances of disturbance sizes at each frequency *** method was demonstrated to accurately model the sizes as well as the corresponding frequencies;thus,the total disturbed area and number of disturbance patches were both accurately *** applying the method to 13 provinces in China,consistent patterns were revealed by the modeling results and remote-sensing-based product,showing that between 2000 and 2005,forests in most provinces were dominated by moderate disturbances(10 ha1000 ha)occurred in the northeastern and northwestern *** study concludes that the proposed method can improve the representation of the size–frequency distribution of forest disturbances.

关键词： Forest disturbance patch size remote sensing forestry

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analysis of city centrality based on entropy weight TOPSIS and population mobility:A case study of cities in the Yangtze River Economic Belt

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Journal of geographical Sciences 2020年第4期30卷 515-534页

作者： LUO Jing CHEN Siyun SUN Xuan ZHU Yuanyuan ZENG Juxin CHEN Guangping Key Laboratory for Geographical Process Analysis&Simulation of Hubei Province Central China Normal UniversityWuhan 430079China The College of Urban&Environmental Sciences Central China Normal UniversityWuhan 430079China Academy of Wuhan Metropolitan Area Hubei Provincial Development and Reform Commission/Central China Normal UniversityWuhan 430079China Institute of Geographic Sciences and Natural Resources Research CASBeijing 100101China School of Earth Sciences Zhejiang UniversityHangzhou 310027China

Based on statistical data and population flow data for 2016,and using entropy weight TOPSIS and the obstacle degree model,the centrality of cities in the Yangtze River Economic Belt(YREB)together with the factors influencing centrality were *** addition,data for the population flow were used to analyze the relationships between cities and to verify *** results showed that:(1)The pattern of centrality conforms closely to the pole-axis theory and the central geography *** axes,corresponding to the Yangtze River and the Shanghai-Kunming railway line,interconnect cities of different *** the whole,the downstream cities have higher centrality,well-defined gradients and better development of city infrastructure compared with cities in the middle and upper reaches.(2)The economic scale and size of the population play a fundamental role in the centrality of cities,and other factors reflect differences due to different city *** most of the coastal cities or the capital cities in the central and western regions,factors that require long-term development such as industrial facilities,consumption,research and education provide the main competitive *** cities that are lagging behind in development,transportation facilities,construction of infrastructure and fixed asset investment have become the main methods to achieve development and enhance competitiveness.(3)The mobility of city populations has a significant correlation with the centrality score,the correlation coefficients for the relationships between population mobility and centrality are all greater than 0.86(P<0.01).The population flow is mainly between high-class cities,or high-class and low-class cities,reflecting the high centrality and huge radiating effects of high-class ***,the cities in the YREB are closely linked to Guangdong and Beijing,reflecting the dominant economic status of Guangdong with its geographical proximity to the YREB and Beijing's e

关键词： city centrality entropy weight TOPSIS population mobility Yangtze River Economic Belt obstacle degree model

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Early Detection of Invasive Phragmites Australis at the Tidal Marsh-Forest Ecotone with Airborne Lidar

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SSRN 2024年

作者： Xiong, Biao Han, Siyuan Messerschmidt, Tyler C. Kirwan, Matthew L. Gedan, Keryn Qi, Man School of Computer Science and Artificial Intelligence Wuhan University of Technology 122 Luoshi Rd Wuhan430070 China Virginia Institute of Marine Science William & Mary Gloucester PointVA United States Department of Biological Sciences The George Washington University WashingtonDC United States Key Laboratory of Geographical Process Analysis and Simulation of Hubei Province College of Urban and Environmental Sciences Central China Normal University Wuhan430079 China

Wetlands across North America are invaded by an introduced lineage of the common reed Phragmites australis, and sea level rise has exacerbated the spread of this species. P. australis at tidal marsh-forest ecotones has rapidly been expanding into deteriorating forest, colonizing understory environments ahead of native marsh species. Early detection of P. australis at the ecotone will be critical to the management of this invasive species in coming decades. In this study, we develop and validate a new method for early detection of P. australis, using open access airborne LiDAR data that can uniquely penetrate the tree canopy and detect P. australis within the forest understory. The method was designed for areas of sparse to moderate tree cover, such as the forest edge where trees are dying and P. australis is expanding, where understory species mapping was previously impossible with most spectral data. To differentiate P. australis from shrubs and other understory herbaceous plants, we tested the effectiveness of several LiDAR-derived spatial metrics, including Mean distance, Point density, Scatter, Omnivariance, and Eigentropy, as inputs to a Support Vector Machine (SVM) classifier, followed by a smoothing algorithm to avoid occasional obstacles or disturbances. We compare among metrics and single- vs. multiple- metric-based classifications. The resulting best early detection method of P. australis achieved a classification accuracy of 91.48% at the development site, and between 56.16% and 80.65% accuracy at other test sites. This algorithm provides a cost-effective and high accuracy method of detecting understory P. australis using public airborne LiDAR data. Larger-scale application of this method will provide coastal resource managers and policy-makers with distribution maps of P. australis through time in open environments and the forest understory. More generally, this approach provides a framework for mapping understory species and plant functional groups usin

关键词： Wetlands

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Tracking Autumn Photosynthetic Phenology of Alpine Grassland on the Tibetan Plateau with Green-Red Vegetation Index

SSRN

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SSRN 2022年

作者： Li, Wangchao Yang, Yajie Chen, Rui Ma, Dujuan Wang, Changjing Wang, Cong Chen, Huai Yin, Gaofei Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu610031 China Key Laboratory for Geographical Process Analysis and Simulation of Hubei Province School of Urban and Environmental Sciences Central China Normal University Wuhan430079 China Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of Biology Chinese Academy of Sciences Chengdu610041 China

Accurate monitoring autumn photosynthetic phenology is essential for understanding carbon cycles. The broadband green-red vegetation index (GRVI) derived from broadband red and green reflectance has been increasingly used in this field. However, the performance of GRVI in large areas remains unclear. We evaluated the performance of the normalized vegetation index (NDVI), normalized difference greenness index (NDGI), solar-induced chlorophyll fluorescence (SIF) and GRVI in tracking autumn photosynthetic phenology of alpine grassland at flux sites and the entire Tibetan Plateau (TP). The results revealed that GRVI (R2 = 0.42, RMSE = 7.32 d and Bias = 4.39 d) performed comparable with SIF (R2 = 0.46, RMSE = 5.16 d and Bias = 0.71 d) in extracting the end of the photosynthetically active season (EOS) with eddy covariance flux measurements as reference. On contrary, a systematically later EOS was estimated by NDVI (Bias = 20.72 d) and NDGI (Bias = 13.62 d). The application example on the TP collaborated these findings. The divergent performances between indicators were rooted in the photosynthesis downregulation in autumn which is jointly controlled by canopy structure and physiology. Our study highlights the unique advantage of GRVI over existing satellite indicators for estimating autumn photosynthetic phenology with high resolution and long-time span. We suggest revisiting the dynamics of autumn photosynthetic phenology using GRVI, which has significant implications on carbon uptake studies. © 2022, The Authors. All rights reserved.

关键词： Vegetation

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A process-Based Deep Learning Hydrological Model for Daily Rainfall-Runoff simulation

SSRN

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SSRN 2023年

作者： Li, Heng Zhang, Chunxiao Chu, Wenhao Shen, Dingtao School of Information Engineering China University of Geosciences in Beijing No. 29 Xueyuan Road Haidian District Beijing100083 China Observation and Research Station of Beijing Fangshan Comprehensive Exploration Ministy of Natural Resources Beijing100083 China Key Laboratory for Geographical Process Analysis & Simulation of Hubei Province Central China Normal University Wuhan430079 China College of Urban and Environmental Sciences Central China Normal University Wuhan430079 China

Rainfall–runoff simulation is an old but still core task of hydrology. Deep learning (DL) models, in particular long-short-term memory (LSTM) neural networks, demonstrate unprecedented accuracy in rainfall-runoff estimation. However, the problem currently is that DL offers few physical explanation beyond its fitting capability. In this study, we developed a process-based DL model. This model implants a process-based ordinary differential equations (ODE) hydrological model into the DL architecture to enable neural networks to obtain process understanding and description of rainfall-runoff similar to process-based models. To implement the model, a simple bucket hydrological model (EXP-HYDRO) is implanted into a common Recurrent Neural Network (RNN) cell and an Entity-Aware LSTM (EA-LSTM) cell is added as a post-processor layer, namely process-based RNN-EA-LSTM (PRNN-EA-LSTM). In PRNN-EA-LSTM, the network structure is represented by the ODE of EXP-HYDRO. simulation accuracy of PRNN-EA-LSTM on the 531 catchments from the Catchment Attributes and Meteorology for Large-sample Studies dataset is almost as good as pure DL models, while maintaining the interpretable model structure like process-based hydrological models. Specifically, the median Nash-Sutcliffe efficiency (NSE) in local and regional rainfall-runoff simulation is 0.70 and 0.72 respectively. In addition, it is also found that PRNN-EA-LSTM surprisingly improves the low-value flows simulations in the runoff hydrograph and reduces the number of catchments with negative NSE, which is difficult to achieve by pure DL models. Therefore, adding physics knowledge to DL models is able to improve simulations, which could be a feasible research direction in the furture research to cognize and simulate hydrology. © 2023, The Authors. All rights reserved.

关键词： Long short-term memory

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